Many well-known biometrics technologies such as automatic facial identification systems (AFIS) have been developed during the past decade and we are now beginning to see their practical deployments in security and surveillance systems. However, video-based AFIS systems suffer difficulties in handling a wide variety of imaging conditions and are very sensitive to variations in lighting conditions and subject orientation. A successful AFIS application often requires the capturing of a well-lit, frontal view facial image. However, as illustrated by the exemplary surveillance image (200) illustrated in FIG. 2, a significant portion of video surveillance images, especially those located in highly secured areas, are acquired by video cameras located to the side of potential subjects (such as in airport tarmac walkway, building hallway, parking lots, and conference/briefing rooms). Consequently, these surveillance images (200) are often partial face images that cause the existing facial identification systems to be vulnerable to mis-identification.
In addition to the above-mentioned challenges, the human face is arguably the most alterable part of the body due to modifiable characteristics such as facial expressions, cosmetics, facial hair, and hairstyle. This ability to alter the appearance of the human face adds to the challenges in utilizing a practical facial identification system as a stand-alone solution to video-based surveillance applications.
Moreover, the capabilities of current biometric human identification systems such as fingerprint, hand geometry, retina scanning, iris, face, and voice recognition are very limited in their surveillance applications. The shortcomings of the current biometric human identification systems include such things as requiring a subject being identified to be cooperative, requiring a subject being identified to be positionally close to the acquisition sensors (for example, the best face identification systems available now can only function when a frontal image is taken within a 15-degree angle of the frontal orientation and within maximum 10 feet distance from the camera), and only being configured to be used for access control rather than for surveillance. Consequently, current biometric human identification techniques at their present sophistication levels cannot meet pressing needs for identifying and tracking human subjects at a distance to enhance personal and building security.
In contrast to the rarely used identification systems illustrated above, remotely controlled video cameras have been widely used for both surveillance and security monitoring. Most video surveillance systems (such as Pan/Tilt/Zoom video cameras) entail a man-in-the-loop to monitor video images and determine if a person displayed on a monitor poses a threat. According to the American Society for Industrial Security (ASIS), there are over 1 million Pan/Tilt/Zoom (PTZ) cameras currently deployed in various surveillance systems in the United States alone. However, many of the existing PTZ cameras are under utilized since they cover only a small portion of a surveyed area at any given time and there are not enough human operators available to manually point the PTZ cameras to track suspicious events and people.
Consequently, a need exists for a surveillance system that improves upon the capabilities of current biometric human identification systems while incorporating already deployed PTZ cameras.